Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy
- DOI
- 10.1007/s00256-026-05370-5
- Published
- 2026-09-14
- Container
- Skeletal Radiology
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s00256-026-05370-5,
title = {Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy},
author = {Mads Hoelgaard Christensen and Rasmus Elsoe and Firaz Mahdi and Mate Hever and Sara Arif-Miscov and Peter Larsen},
year = {2026},
journal = {Skeletal Radiology},
doi = {10.1007/s00256-026-05370-5},
url = {https://doi.org/10.1007/s00256-026-05370-5}
}RIS
TY - JOUR TI - Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy AU - Mads Hoelgaard Christensen AU - Rasmus Elsoe AU - Firaz Mahdi AU - Mate Hever AU - Sara Arif-Miscov AU - Peter Larsen PY - 2026 JO - Skeletal Radiology DO - 10.1007/s00256-026-05370-5 UR - https://doi.org/10.1007/s00256-026-05370-5 ER -
APA
Christensen, M. H., Elsoe, R., Mahdi, F., Hever, M., Arif-Miscov, S., & Larsen, P. (2026). Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy. Skeletal Radiology. https://doi.org/10.1007/s00256-026-05370-5
Source records
- crossref · retrieved 2026-09-25T20:54:56.647Z